BierOne's repositories
bottom-up-attention-vqa
An updated PyTorch implementation of hengyuan-hu's version for 'Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering'
ood_coverage
[ICLR 2024 Spotlight] Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
Attention-Faithfulness
[ICML 2022] This is the pytorch implementation of "Rethinking Attention-Model Explainability through Faithfulness Violation Test" (https://arxiv.org/abs/2201.12114).
relation-vqa
Re-implementation for 'R-VQA: Learning Visual Relation Facts with Semantic Attention for Visual Question Answering'.
VQA-AttReg
This is an official PyTorch implementation of “Answer Questions with Right Image Regions: A Visual Attention Regularization Approach” (https://arxiv.org/abs/2102.01916).
policy_privacy_benchmarks
This is a pytorch implementation for state-of-the-art results on policy privacy datasets (OPP-115).
genome-rcnn-features-for-bottom-up
This repository supplies the visual-genome features of bottom-up-attention
diffusers-interpret
Diffusers-Interpret 🤗🧨🕵️♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.
Interpretable-Attention
Official Code for Towards Transparent and Explainable Attention Models paper (ACL 2020)
negative_analysis_of_grounding
A negative case analysis of visual grounding methods for VQA (ACL 2020 short paper)
EasyEdit
An Easy-to-use Knowledge Editing Framework for LLMs.
KnowledgeEditing_Benchmarks
This repository serves as a comprehensive resource for researchers interested in exploring Knowledge Editing. Here, you'll find detailed comparisons and information about various benchmarks/datasets relevant to this domain.
stable-diffusion-webui
Stable Diffusion web UI
Transformer-MM-Explainability
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.